Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application

Learn how to use autoencoders to develop a fraud detection application

Implement LSTM and CNN models using DeepLearning4j and MXNet

About

Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development.

If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet.

At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.

Authors

Md. Rezaul Karim

Md. Rezaul Karim is a Research Scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Aachen, Germany. He has more than 8 years' experience in the area of research and development with a solid understanding of algorithms and data structures in C, C++, Java, Scala, R, and Python.

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